MS Excel: Statistics and Data Analysis

Perform Statistical analysis beginning from descriptives to hypothesis testing using MS-Excel Analysis Toolpak
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  • Lectures 30
  • Length 1.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
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About This Course

Published 2/2016 English

Course Description

Present day organizations are data driven. Starting from Start-ups to Conglomerates every organization is relying on data for decision making. Organizations are flooded with data from multiple facets (websites, social network sites, third party data sources, daily operational data etc). Skimming this data to get meaningful information has become daunting task for organizations. They are looking for skilled manpower who can convert this gigantic data into sleek information for decision making. This course is for the beginners who wish to test the water in Data Analytics.

This course fuses Statistical Analysis with MS Excel because of which you would be able to churn legions of data into meaningful information within no time. Excel has hundreds of built-in functions and Data Analysis Toolpak (Excel Add-in) with which you can run descriptive statistics to predictive analysis with ease. In this course I created videos that help you understand statistical concepts and solve complex equations using Excel. Excel Workbooks are provided to you for practice and master the concepts.

What are the requirements?

  • Quest to analyze legions of Data
  • An understanding of Excel

What am I going to get from this course?

  • Design, Develop and administer questionnaires, Collect data from different sources, Enhance ability to analyze data, and Derive inferences to take successful decisions. Data Analysis speed and accuracy will enhance 10x.

Who is the target audience?

  • Students who want to pursue career as Data Analyst, Data Scientist, Research Associates
  • Social Science students who want to do empirical research report/ Project Assignment / Thesis
  • Business Management Students (all streams)
  • Research Scholars / Research Students of Social Sciences and Business Management
  • All professionals who want to turn data into information
  • Entrepreneurs who wants to leverage of Data

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction to the Course

Know what is there in this course for you. For whom this course is and how are you going to benefitted from this course.

Section 2: Statistics - Understanding the Basics

Organizations expect you to perform statistical analysis on your own. You need to crunch data as per your requirements. As you work in intense competitive work environment you don’t have a luxury to take days and days to crunch data.A strong theoretical knowledge of statistics is not suffice, you should also be able to collect, organize, visualize and analyze data with Software.

In this course you will learn how to design a research project, source data, clean data, perform data analysis with MS-Excel, interpret results, and complete research assignment in stipulated time frame.

Along with video lectures, you are provided with pdf notes and Excel work sheets to practice the learning.


In this lecture you will learn the DCOVA frame work. You are introduced to Design, Collection, Organizing, Visualizing, and Analyzing Data.

This lecture is vital for your research projects. Majority of research projects commence with an well articulated to research plan.


On completion of this lecture you will be able to differentiate descriptive stats with inferential stats.

In this lecture you will learn about Variable Types and what statistical techniques should be run on different variable types

Learn about types of Variables or Data Sets and pertinent statistical tools for each type of data set.

In this lecture you are introduced to univariate, bivariate, and mutlivariate data sets. And what types of charts and statistical techniques need to be used for each data set type is also explained.


Get familiar with measurements of scales in statistics. You will learn about - Nominal Scale, Ordinal Scale, Interval Scale and Ratio Scale.

I will also learn how and when to use each measurement scale to source the data.


In this lecture I will introduce you to Primary Data sources (experimental, observational, and survey data), and also to Secondary Data sources (Distributed data, Data from daily business activities)

Section 3: Sort Data and Draw Random Samples
Learn how to Sort data and create Filters in MS-Excel. This lecture would be a great help in drawing random samples from large population.

Learn how to sort data using column heading and create advanced filters in MS-Excel.


Learn how to draw cluster random sample with the help of MS-Excel by using highly clustered real time large data set.

Learn how to draw stratified random sample using MS-Excel built-in tools and make your sample proxy for population.
Section 4: Data Presentation

Learn how to create charts to identify trends, clusters, extreme values using MS-Excel Chart Wizard.

Drawing charts is the first step in your data presentation. With MS-Excel you can create eye catching charts and present your data in vibrant way.

You are introduced to different chart types like, column, line, bar, scatter, stock etc. and when to you which chart type.

Section 5: Descriptive Statistics

Data Analysis Toolpak is an Excel add-in program. However, you need to load it manually. Once you load the Data Analysis Toolpak, a Data Analysis command button will appear under Data menu ribbon.

With the help of Data Analysis command button you can run many statistical tools like, histograms, correlation, regression, anova, t-test, independent t-test, moving averages, exponential smoothing etc, with writing any formulas.

Irrespective of the size of your data, you can run the analysis in few minutes.


Compute descriptive statistics methods like Mean, Median, Mode, Variance, Standard Deviation,

Skewness, and Kurtosis in few clicks with the help of MS-Excel Data Analysis command. It takes just a minute to calculate all the descriptives, irrespective of number of records or data points.


Calculate grouped frequency distribution, cumulative percentage, histogram, and normal curve chart with MS-Excel Data Analysis command.


In this lecture you will learn The Empirical Rule and Tests of Normality. Also learn how to interpret the standard deviation, and test normality of data using Skewness and Kurtosis.

Section 6: Bivariate Analysis (Correlation Analysis)

The first step in understanding the relationship between two variables is to plot the data on scatter plot. In this lecture you will learn how to draw a scatter plot and fit trend line on Bivariate data set.


Correlation is used to find out relationship between Bivariate and multivariate data sets. In this lecture you will learn how to compute correlation value (s) and interpret them. Also learn various types of relationships.

Correlation and Cross-order correlations are computed with the help of MS-Excel Data Analysis command.

Section 7: Casual Relationship (Regression Analysis)

Regression analysis is most widely used predictive analysis technique. In this lecture you will learn how to predict or forecast using regression analysis.


Learn and compute Regression analysis to quantify the relation, direction, and strength between two variables. Regression measures the relationship between two variables i.e. Independent or Predictor variable, and Dependent or Criterion variable. With MS-Excel Data Analysis command you solve the regression equation with few click.

Along with regression analysis you can also test the hypothesis and strength of the relationship.
Section 8: Multiple Linear Regression Analysis

Multiple regression analysis is most widely used technique in predictive analytics. Multiple regression equation is an extension of simple regression equation.

Y = b0+b1X1+b2X2+b3X3+…..+e.

You don’t need to worry about the complexity of solving the above equation. Using MS-Excel Data Analysis – Regression command you can solve it within no time.

Multiple regression analysis allows you to fit a more sophisticated model with several variables that explain a dependent variable. You use separate casual factors, analyzing each one’s influence on what you are trying to explain. Learn and practice multiple regression analysis.

Section 9: Time Series Data Analysis

Learn how to analyze Time series data to discover a pattern or trend in the historical data and extrapolate the pattern into the future.

In this lecture you will learn how to compute Simple Moving average using MS-Excel built-in function.


Exponential smoothing is a simple and pragmatic approach to quantitative forecasting that researchers found useful due to its short-term precision and cost effectiveness. In exponential smoothing the forecast is constructed from an exponentially weighted average of historical data.

Learn how to Calculate exponential smoothing is with Excel Data Analysis command.

Section 10: Hypothesis Testing - Two Samples

Learn how to test the hypothesis of similarity and dissimilarity between two paired samples. You are also introduced to frame null and alternative hypothesis.

Context, assumptions, and interpreting the test results are also explained.


The independent samples t-test evaluates the difference between the means of two independent or unrelated groups. The t-test evaluates whether the mean value of the test variable for one group differs significantly from the mean value of the test variable for second group.

Compute independent t-test with the help of MS-Excel Data Analysis tool.
Section 11: Hypothesis Testing - Three or More Variables Analysis of Variance (ANOVA)
In this lecture you are introduced to the assumptions, advantages and disadvantages of One-Way ANOVA. Also know the context in which you need to use ANOVA to test the hypothesis.

ANOVA test is conducted to test whether there exists any difference among three or more groups of data. Manually calculating ANOVA is time consuming and tedious.

Using MS-Excel data analysis command you can compute it quickly and accurately. In this lecture you will learn the relevance of ANOVA test, its context, assumptions, framing null and alternative hypothesis, running the analysis and interpreting the results.
Section 12: Chi-Square Test (Non Parametric) for Categorical Data

In this lecture you will learn how to test for independence of two categorical or grouping variables. In MS-Excel you don’t have a direct function or tool to perform the chi-square test. After attending this lecture you would be able to compute chi-square test in MS-Excel.

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Instructor Biography

Prof. Rama Krishna Yelamanchili, Professor of Quants at RK Business School, Hyderabad, India

I am teaching Quants for Decision Making for over 15 years. As the speed and accuracy plays pivotal role in data analysis and decision making, most of my teaching relies on Statistical Softwares (Excel, Data Analysis Toolpak, SPSS, E-Views, StatPro, etc.). I fuse concepts with computers with ease. After attending my classes students are able to analyze the data in short time, and spend lot of time on interpreting the results and drawing inferences to make promising decision.

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